18523102. SELF-TRACKED CONTROLLER simplified abstract (Meta Platforms Technologies, LLC)

SELF-TRACKED CONTROLLER

Organization Name

Meta Platforms Technologies, LLC

Inventor(s)

Samuel Redmond D'amico of San Francisco CA (US)

SELF-TRACKED CONTROLLER - A simplified explanation of the abstract

This abstract first appeared for US patent application 18523102 titled 'SELF-TRACKED CONTROLLER

Simplified Explanation

The disclosed system includes a housing with components such as a physical processor, sensors, and a camera. The system also has physical memory with instructions for the processor to acquire images, identify features, generate a map, access sensor data, and determine the system's pose in the environment.

• Components of the system: housing, physical processor, sensors, camera, physical memory
• Functions of the physical processor: acquire images, identify features, generate a map, access sensor data, determine system's pose
• Instructions stored in physical memory for the processor to perform the functions

Potential Applications

The technology could be used in autonomous vehicles, robotics, surveillance systems, and mapping applications.

Problems Solved

The system helps in mapping and navigating an environment, identifying features, and determining the system's position accurately.

Benefits

The system provides accurate mapping and navigation capabilities, enhances situational awareness, and improves decision-making processes.

Potential Commercial Applications

The technology could be applied in autonomous vehicles for navigation, surveillance systems for security purposes, robotics for mapping environments, and mapping applications for creating detailed maps.

Possible Prior Art

One possible prior art could be similar systems used in autonomous vehicles or robotics for mapping and navigation purposes.

How does the system handle dynamic environments?

The system's ability to adapt to changes in the environment, such as moving objects or changing conditions, is not explicitly mentioned in the abstract. This could be a crucial aspect to consider for real-world applications where the environment is not static.

What is the accuracy of the system in determining the system's pose?

The abstract does not provide details on the accuracy of the system in determining the system's pose in the environment. Understanding the level of precision and reliability of the system's pose estimation could be essential for certain applications where accuracy is critical.

Original Abstract Submitted

The disclosed system may include a housing dimensioned to secure various components including at least one physical processor and various sensors. The system may also include a camera mounted to the housing, as well as physical memory with computer-executable instructions that, when executed by the physical processor, cause the physical processor to: acquire images of a surrounding environment using the camera mounted to the housing, identify features of the surrounding environment from the acquired images, generate a map using the features identified from the acquired images, access sensor data generated by the sensors, and determine a current pose of the system in the surrounding environment based on the features in the generated map and the accessed sensor data. Various other methods, apparatuses, and computer-readable media are also disclosed.